Data Science & Analysis

AI and ML Course

Build deep predictive models. Master mathematical regressions, classifiers, neural network pathways, and model hosting using TensorFlow and PyTorch in an offline classroom environment.

Course Overview

Artificial Intelligence is changing the shape of global technology. From recommendations engines to large language models, smart algorithms are rewriting how enterprises function. This offline program at 3Stack Academy equips you with the statistical design skills and vector math necessary to create, validate, and host deep prediction systems.

We avoid pre-packaged visual model-builders. In this classroom, you will write ML algorithms from scratch in Python to understand cost functions, gradients, and model weights. You will learn to clean complex training directories, evaluate structures using precision-recall metrics, train neural network layers using TensorFlow and PyTorch, and deploy predictive APIs on cloud servers.

Course Syllabus

Module 01: AI Foundations — Discover the Technology Powering the Future
  • What is Artificial Intelligence? • History & Evolution of AI • AI vs Machine Learning vs Deep Learning
  • Real-World Applications of AI • AI in Healthcare, Finance, Education & Business
  • AI Ethics • Responsible AI
Module 02: Python for Artificial Intelligence — Build the Programming Foundation for AI Development
  • Python Refresher • Variables & Data Types • Functions • OOP Concepts
  • NumPy • Pandas • Data Visualization with Matplotlib & Seaborn
  • Jupyter Notebook • Google Colab
Module 03: Mathematics for AI — Understand the Mathematical Concepts Behind Intelligent Systems
  • Linear Algebra Fundamentals • Probability & Statistics • Mean, Median & Standard Deviation
  • Vectors & Matrices • Basic Calculus • Distance Metrics
  • Mathematical Foundations for AI Models
Module 04: Data Preprocessing — Transform Raw Data into AI-Ready Data
  • Data Collection • Understanding Data Quality • Cleaning Missing Values
  • Handling Outliers • Data Transformation • Feature Scaling
  • Label Encoding • Preparing Features & Labels • Train-Test Split
Module 05: Machine Learning Fundamentals — Teach Machines to Learn from Data
  • Machine Learning Workflow • Types of Machine Learning • Features & Labels
  • Training & Testing Data • Model Training • Model Prediction
  • Model Evaluation • Cross-Validation • Understanding Bias & Variance
Module 06: Supervised Machine Learning — Build Models That Learn to Predict and Classify
  • Linear Regression • Logistic Regression • Decision Trees • Random Forest
  • K-Nearest Neighbors (KNN) • Support Vector Machine (SVM)
  • Regression & Classification Problems • Model Comparison • Performance Evaluation
Module 07: Unsupervised Machine Learning — Discover Hidden Patterns and Groups within Data
  • Introduction to Clustering • K-Means Clustering • Hierarchical Clustering
  • Principal Component Analysis (PCA) • Dimensionality Reduction
  • Anomaly Detection • Pattern Discovery • Customer Segmentation Project
Module 08: Deep Learning & Neural Networks — Explore the Technology Behind Modern AI Systems
  • Introduction to Deep Learning • Neural Networks • Artificial Neurons
  • Layers & Network Architecture • Activation Functions • Forward Propagation • Backpropagation
  • Introduction to TensorFlow • Keras • Building Your First Deep Learning Model
Module 09: Natural Language Processing (NLP) — Teach Machines to Understand Human Language
  • Introduction to NLP • Text Cleaning & Preprocessing • Tokenization
  • Word Embeddings • Text Representation • Sentiment Analysis • Text Classification
  • Understanding Conversational AI • Building a Basic Chatbot
Module 10: Computer Vision — Teach Machines to Understand Images and Visual Information
  • Introduction to Computer Vision • Image Processing Fundamentals • OpenCV
  • Working with Images • Image Classification • Face Detection • Object Detection
  • Working with Camera Inputs • Building Real-Time Computer Vision Applications
Module 11: Generative AI & Large Language Models — Build Intelligent Applications with Modern Generative AI
  • Introduction to Generative AI • Understanding Large Language Models (LLMs)
  • Prompt Engineering • Effective Prompt Design • Working with AI APIs • OpenAI APIs
  • Hugging Face Basics • Introduction to Pre-Trained Models • AI Assistants • Building AI Chatbots
Module 12: AI Deployment & Production — Take Your AI Models from Development to Real-World Applications
  • Model Serialization • Saving & Loading AI Models • Streamlit Basics
  • Building Interactive AI Applications • Introduction to Flask & FastAPI • Creating APIs for AI Models
  • Deploying AI Models • Git & GitHub • Version Control • Model Hosting • Production AI Applications

Career Opportunities & Job Roles

AI positions command premium salaries. Students demonstrating advanced project competence are directly referred for development internships at Greycrust Solutions.

Machine Learning Engineer
Average Package: ₹9 LPA – ₹18 LPA
Design custom data training feeds, optimize model hyperparameters, deploy ML microservices, and manage inference loops.
NLP Engineer
Average Package: ₹8 LPA – ₹15 LPA
Integrate LLMs, construct custom semantic search vector databases, and implement text analysis modules.
Computer Vision Developer
Average Package: ₹8.5 LPA – ₹16 LPA
Develop object-detection classifiers, image parsing pipelines, and video diagnostics routines in PyTorch.
Junior AI Research Scientist
Average Package: ₹10 LPA – ₹20 LPA
Propose algorithm variations, validate mathematical structures, and write model benchmark tests for client systems.
Deep Learning Specialist
Average Package: ₹9 LPA – ₹17 LPA
Construct deep neural layers, compile convolution networks (CNN), and manage backpropagation training routines.
Data Model Evaluator
Average Package: ₹6 LPA – ₹10 LPA
Validate dataset parameters, inspect training biases, check inference output latency, and audit model precision-recall rates.
AI Solutions Architect (Associate)
Average Package: ₹10 LPA – ₹18 LPA
Design server structures, model memory bounds for inference, and architect custom API flows.
Algorithm Engineer
Average Package: ₹8.5 LPA – ₹15 LPA
Clean data math flows, translate raw vectors, and compile neural structures to run on hardware accelerated environments.